Adaptive Robust Control Free-Floating Space Robotic Manipulators based on RBF Neural Network

Abstract

Problems of trajectory tracking of the free-floating space robotic manipulators model with uncertainties are studied. An adaptive robust control algorithm of space manipulators based on radial basis function neural network (RBFNN) is proposed by the paper. Neural network controller is used to adaptive learn and compensate the unknown system, approach errors as disturbance are eliminated by robust controller. The weight adaptive laws on-line based on Lyapunov theory can ensure stability of system. The robust controller was proposed based on H∞ theory. Above these assured the stability of the whole system, and L2 gain also was less than the index. This control scheme possesses great control accuracy and dynamic function. The simulation results show that the presented neural network control algorithm is effective.